Attending physician workload is an understudied area of research and may be compromising the safety and quality of patient care. Staffing and patient safety has only been examined for resident-physicians and nurses, neglecting the attending or supervisory physicians' role. The overall objective of this research is to study hospitalists to determine factors affecting attending physician workload, examine the association between attending workload and patient outcomes, and engage stakeholders to develop strategies to minimize the adverse effects of workload. This research aims (1) to determine and characterize the current patient:hospitalist ratio, its perceived safety, and related workload factors using a statewide hospitalist survey; (2) to examine the typical patient:hospitalist ratio in seven hospitas within a regional healthcare network, and its variability and impact on national and state-wide patient safety and quality of care performance measures, including patient satisfaction; and (3) to engage the various stakeholders using the Delphi technique to understand the contextual factors of workload and develop and prioritize strategies to minimize the adverse effects of workload. This research will establish a foundation for describing safe hospitalist workload, the factors related to workload, and the impact of workload on patient safety and quality of care. The candidate is a Hospitalist and Assistant Professor within the Division of General Internal Medicine at Johns Hopkins University School of Medicine. His primary mentor is Dr. Peter Pronovost, Director of the Armstrong Institute for Patient Safety and Quality. His secondary mentor is Dr. Daniel Ford, Director of the Institute for Clinical and Translational Research. Both mentors are established health services investigators with extensive mentorship experience. The candidate's long-term goal is to become an independent health services researcher with expertise in inpatient safety and quality of care. To accomplish this, his short-term goals involve a career development plan to advance his skills in, and provide field experience for, (1) developing, administering, and analyzing large national surveys, including the use of factor analysis; (2) collecting, managing, and analyzing hierarchical quality and patient safety data, and using multi-level modeling to distinguish between provider and system-level effects; and (3) understanding performance metrics, the economic and workforce implications, and the contextual factors which can undermine quality improvement initiatives in order to engage stakeholders and effect change. During the Career Development Award, the candidate will combine parallel lines of investigation, including surveys, administrative data analysis, and stakeholder engagement, culminating in an evidence-based hospitalist healthcare delivery model designed to optimize provider workload and patient care (R01). Results from this proposal will have broad implications for measuring, understanding, and improving the workload of numerous physician specialties, and provide a foundation upon which to base interventions, make recommendations, and engage stakeholders.